In recent years, numerous network applications have resulted in streams being defined over massive graph infrastructures. In such applications, the entire graph is not available at one time, but individual edges are received rapidly over time in the form of a stream. Furthermore, the number of vertices in the graph is very large, so that it becomes very difficult to store the edges in the graph in an efficient way.
It is often desirable to query and mine such massive graph streams, and the key is to summarize the behavior of graph streams accurately and effectively. However, mining graph streams in which the data is too large to be stored even on disk poses particular challenges since the entire data cannot be explicitly stored for querying purposes.